Yashwant Kashyap, Ankit Bansal and Anil K. Sao
The presence of broken clouds leads to frequent fluctuations in direct normal incident solar irradiation as well as diffuse radiation from the sky. This brings a lot of challenge…
Abstract
Purpose
The presence of broken clouds leads to frequent fluctuations in direct normal incident solar irradiation as well as diffuse radiation from the sky. This brings a lot of challenge for grid integration of solar power plants. The paper aims to discuss this issue.
Design/methodology/approach
A new model is presented to nowcast solar radiation by utilizing hourly global horizontal irradiance (GHI) over a large spatial grid. The spatial distribution of the GHI provides information on the presence of a cloud shadow above a given site. This information is extracted with the help of various data processing techniques. The spatial–temporal data analysis is employed to track the extracted cloud shadow image based on a dynamic model. A Kalman filter is applied for the assimilation of data in the tracking of the extracted shadow over a geographical location.
Findings
The proposed model can provide very good forecasting of solar radiation for various time horizons. However, the variation of shadow features between time steps must be included in the dynamic model to forecast accurate GHI values.
Research limitations/implications
In this paper database used is on hourly basis; it can be further improved for the inter-hour level of ground data for more accuracy.
Practical implications
The outcome of this paper would be useful in the field of solar energy application and for weather monitoring purposes.
Originality/value
The forecasted position of the shadow is utilized to prepare and forecast a GHI map for one hour time horizon. Results show that the model can be utilized to forecast solar radiation with accuracy consistent with the contemporary models.
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Guilherme F. Frederico, Vikas Kumar, Jose Arturo Garza-Reyes, Anil Kumar and Rohit Agrawal
This study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their…
Abstract
Purpose
This study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their interoperability can create pathways for SCs resilience post-COVID-19. This is of paramount importance in the context of COVID-19 as the investigation around I4.0 technologies may provide relevant insights on how SCs may better respond to unexpected situations like the current pandemic with the use of digital technologies.
Design/methodology/approach
A survey research method was designed based on some constructs extracted from the literature regarding the main disruptive technologies, interoperability, elements of supply chains processes (SCPs) performance such as integration, collaboration, transparency, efficiency, responsiveness and profitability. The data were collected from March to July 2020 from different regions of the world when the peak of the first wave of the pandemic had occurred. The survey resulted in 115 valid responses. The study used a combination of descriptive, correlation and multiple regression methods to analyse the data.
Findings
The study indicates that disruptive technologies significantly impact SCPs performance (integration, collaboration, responsiveness and transparency) and their resilience. The findings did not support the notion that these technologies improve the efficiency of SCs, a significant contrast to the existing literature. Our findings also refute the existing understanding that interoperability moderates the impact of disruptive technologies on SCPs performance and enhancing the resilience of SCs. However, the findings show that the integration of I4.0 technologies and their interoperability has a positive impact on SCPs profitability.
Research limitations/implications
The findings strongly advocate that this integration plays an important role in improving SC performance, and a future pathway of SC resiliency post-COVID-19. Considering that the I4.0 trend will impact SCs in the coming years, this study brings a relevant contribution to researchers and practitioners.
Originality/value
This study makes a unique contribution by investigating a novel causal relationship between the main elements (I4.0 technologies, interoperability, processes performance and strategic outcomes) related to the SC in this new context.
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Danilo Soares Silva, Gustavo Hermínio Salati Marcondes de Moraes, Ieda Kanashiro Makiya and Francisco Ignácio Giocondo Cesar
This study aims to find evidence of the HEdPERF scale use for measuring the perceived service quality from the perspective of students in higher education institutions (HEIs…
Abstract
Purpose
This study aims to find evidence of the HEdPERF scale use for measuring the perceived service quality from the perspective of students in higher education institutions (HEIs) worldwide.
Design/methodology/approach
A systematic review of the literature was conducted to find evidence of the scale use in articles published between January 2005 and May 2017, according to databases Emerald, SciELO, Scopus, Web of Science, and Wiley Online Library. The articles were searched on the databases on Jun 17, 2017 and at the end of the selection of articles, were kept 12 distinct documents.
Findings
The articles found pointed towards classic SERVQUAL and SERVPERF scales as being well substantiated for measuring perceived service quality. The HEdPERF scale was applied in articles about perceived service quality in HEI in studies in Brazil, China, Croatia, India, Malaysia, Portugal, Sri Lanka and Turkey.
Originality/value
The paper attempts to gather some articles on the measurement of service quality in higher education institutions, by the HEdPERF scale use. This study indicates that SERVPERF scale can also be an appropriate model to measure service quality in HEI context, that is, it is not yet possible to defend a single instrument as a standard for this purpose.
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Guilherme F. Frederico, Vikas Kumar, Jose Arturo Garza-Reyes, Roberto A. Martins and Anil Kumar
Yuvika Gupta, Farheen Mujeeb Khan, Anil Kumar, Sunil Luthra and Maciel M. Queiroz
With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research…
Abstract
Purpose
With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.
Design/methodology/approach
Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.
Findings
The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.
Research limitations/implications
This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.
Originality/value
The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.
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Hugo Gobato Souto and Amir Moradi
This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility…
Abstract
Purpose
This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.
Design/methodology/approach
Employing a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.
Findings
The research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)
Originality/value
This paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.
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Antônio Jeovah de Andrade Meireles, João Alfredo Telles Melo and Magnólia Azevedo Said
The present study evaluates the principal forms of socioenvironmental damage suffered by local traditional populations and indigenous communities as a result of the installation…
Abstract
The present study evaluates the principal forms of socioenvironmental damage suffered by local traditional populations and indigenous communities as a result of the installation and operation of the Pecém Industrial and Shipping Complex. The main problem being pollution in the municipalities of São Gonçalo do Amarante and Caucaia, which is in the Brazilian state of Ceará. As a theoretical framework, we use the concept of “environmental justice,” and “environmental racism.” The latter were used to understand the process of “deterritorialization” of these communities that resulted in extensive impacts on the natural environment, as well as the way of life and productive practices of these communities. Our analyses confirm the destruction of the means that allow noncapitalist exploitation of natural resources, such as artisanal fisheries, subsistence farming, and the use of commons. We show how all these processes are constitutive of environmental injustice and environmental racism. These may contribute to the organization of the resistance and struggle of the affected populations, namely indigenous peoples and traditional communities.
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Harsimran Riar, Sunil K. Khatkar, Anju Boora Khatkar, Nishant Arora, Sandeep Mann, Anil Panghal and Sanjeev Kumar
The purpose of the study is to highlights the conceptual and scientific knowledge regarding bioavailability of food bioactive components which is essential for the thorough…
Abstract
Purpose
The purpose of the study is to highlights the conceptual and scientific knowledge regarding bioavailability of food bioactive components which is essential for the thorough understanding of their role in disease prevention and factors that limit their absorption.
Design/methodology/approach
Nutrikinetics is an extended version of pharmacokinetics that is used for studying the bioavailability and bioaccessibility of components through different techniques such as metabolic profiling, multi-level data analysis and population-based modeling.
Findings
There are different phases of nutrikinetics study of the bioactive components. The initial stage of nutrikinetics is starting from simplest in-vitro assay which is applicable in the early stage of functional foods development. Thereafter, the next stage of nutrikinetics studies are related to human intervention studies as designed by European Food Safety Authority. The aim of such studies are to develop dose-exposure and exposure response study of a bioactive component.
Originality/value
This paper will enlighten the concept of nutrikinetics, its requirement and the future perspectives of nutrikinetics study including long-term efficacy studies and multi-compartmental analysis of the different bioactive components.
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Bárbara Schausteck de Almeida, Juliano de Souza and Wanderley Marchi Júnior
The purpose of this study is to evaluate the after-sales strategy of an industrial equipment manufacturer.
Abstract
Purpose
The purpose of this study is to evaluate the after-sales strategy of an industrial equipment manufacturer.
Design/methodology/approach
The research study’s object is the Brazilian operation of a company belonging to a multinational group that designs, manufactures and installs technology-based equipment. The research method is qualitative modeling with a quantitative analysis. A literature review and a focus group with managers organized the after-sales strategy of the company in four constructs measured by 24 indicators. The constructs are technical assistance (TA), reliability management (RM), customer relationships (CRs) and spare part logistics (SL). A total of seven managers evaluated the importance and performance of the indicators.
Findings
TA, RM and CRs are lagging constructs (the importance is greater than the performance), whereas SL is a leading construct (the opposite). The study proposed four strategic actions that change the type of emphasis that the company poses to service: from in-house to field maintenance service, from correction to prevention reliability improvement, from technical- to customer-focused relationships and from direct to integrated logistics service.
Research limitations/implications
The study limits to the case of a technology-based manufacturing company.
Practical implications
The strategic movement reallocates resources from leading indicators to lagging indicators in a sharp, clear movement of forces in the company.
Originality/value
The main contribution is a structured method to evaluate and control the strategic performance of an industrial equipment manufacturer in after-sales activities.